NEWS17 September 2026A new system will help scientists to refine large language models for longevity research and clarify ‘biological’ age.ByHeidi Ledford0Heidi LedfordHeidi Ledford reports for Nature from Seattle, Washington.View author publicationsSearch author on: PubMed Google ScholarSave articleView saved researchSome individuals have a ‘biological age’ that is younger than their chronological age.Credit: Karen Haibara/AFP/GettyUnderstanding why people age — and how to slow that process down — is an obsession that has stretched across millennia, from mythic quests for immortality to modern science’s hunt for drugs that lengthen lifespan.Now, that quest has entered into the AI era.A report1 published today in Cell unveils a bespoke artificial-intelligence system that aims to turbocharge longevity research. The system introduces large language models (LLMs) that the authors trained on ageing-biology data. It also includes a suite of 17 tasks that can serve as benchmarks to gauge how well these and other LLMs perform on ageing-related projects. Finally, it includes an interface that brings the models and other ageing-related research tools together with AI assistants called agents to aid analyses.Gene clock predicts time to death in humans — and assesses ‘biological’ ageThe authors used their benchmarks to evaluate both their specialist LLMs and much larger cutting-edge commercial models produced by companies including OpenAI and DeepSeek, that are trained on larger, more diverse datasets to handle a broad range of tasks. In many — although not all — of the tests, the LLMs tailored to ageing research outperformed the large LLMs.“The paper makes a very important contribution to the longevity and ageing field,” says Marinka Zitnik, a computer scientist at Harvard Medical School in Boston, Massachusetts, who was not involved in the work. “It can inform the development of next-generation AI models.”The work also tackles a key question for the field: how can researchers train AI tools to understand ageing when scientists have not yet defined the concept for themselves? “For certain disease areas, such as cancer, the AI tasks can be very crisply defined,” says Zitnik. “Ageing is a very different beast. It is hard to define.”Clock collectorsResearchers have spent decades gathering data to define that beast. One result has been a slew of ‘clocks’ aimed at measuring biological ageing, or the rate at which a person’s body exhibits signs of ageing. Such clocks measure biological age by assessing characteristics such as facial features, protein levels, gene activity and brain scans, all with the goal of quantifying whether the effects of ageing are outpacing or lagging behind someone’s chronological age in years.How quickly are you ageing? What molecular ‘clocks’ can tell you about your healthBut even as the clocks increase in sophistication, researchers are still not certain how to interpret their results. Last week, a group of researchers reported2 that an experimental drug against a lung disease had lowered the biological age of recipients in a small clinical trial. The result was based on six different ageing clocks, yet researchers struggled to conclude whether the drug truly reversed the fundamental processes of ageing, or if it merely improved overall health.It's a conundrum that isn't just limited to that study. “Where does ageing end, or disease start?” asks Chiara Herzog, an epigeneticist at the University of Cambridge, UK. “How do you disentangle that? It’s not really clear.”Researchers hope that AI can help to develop better clocks and identify new molecular hallmarks of ageing. But scientists also need new ways to gauge how well their AI tools are working, says Qian Di, a data scientist who studies public health at Tsinghua University in Beijing. “The central task now is to test how 'smart' the AI is,” he says.doi: https://doi.org/10.1038/d41586-026-02913-7ReferencesZhavoronkov, A. et al. Cell https://doi.org/10.1016/j.cell.2026.08.026 (2026).Article Google Scholar Zhavoronkov, A. et al. Nature Biotechnol. https://doi.org/10.1038/s41587-026-03286-y (2026).Article Google Scholar Download references World-first: therapy to make cells young again trialled in a person Sleep linked to slower ageing: huge study pinpoints the right amount Ageing accelerates around age 50 ― some organs faster than othersSubjectsAgeingMachine learningLatest on:AgeingMachine learningJobs Associate or Senior Editor, Nature Communications (Polymer Materials)Title: Associate or Senior Editor, Nature Communications (Polymer Materials) Locations: Shanghai, Beijing, Nanjing, New Delhi or Pune (Hybrid) Appl...Shanghai, Beijing, Nanjing, New Delhi or Pune (Hybrid)Springer Nature LtdAssociate or Senior Editor (Sustainable materials chemistry)Title: Associate or Senior Editor, Nature Portfolio (Sustainable Materials Chemistry) Locations: Shanghai, Beijing, Nanjing, New Delhi or Pune (Hyb...Shanghai, Beijing, Nanjing, New Delhi or Pune (Hybrid)Springer Nature LtdAssociate or Senior Editor, Communications PhysicsJob title: Associate or Senior Editor, Communications Physics Locations: Shanghai, Beijing, Berlin, Heidelberg , Pune (hybrid) Closing date: Sept 3...Shanghai, Beijing, Berlin, Heidelberg , Pune (hybrid)Springer Nature LtdPhD Candidate (m/f/d)This position is part of the Leibniz Science Campus “Cardio-Oncology Campus for Precision Medicine”.Dortmund, Nordrhein-Westfalen (DE)Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V.